Documents » iterative versusersurecursive queries.
Abstract: Traditional analytic tools run
queries against a data warehouse (DW) with user
queries being processed against the data stored on relatively slow hard drives. In-memory analytics leverages a significantly more efficient approach where all the data is loaded into memory. This results in dramatic improvements in query response time and end-user experience. Find out how in-memory analytics can help your organization.
PubDate: 4/9/2010 12:27:00 PM
Abstract: Mid-market and the SMB segment are the next frontiers and a promised land for all the enterprise vendors, small and large alike.Still, the willingness of smaller IT departments to go for more sophisticated technology beyond the all-too-common dispersed islands of information on Excel spreadsheets, Access-based reports and queries, or even managers’ pocket paper-pads and post-it notes, does not guarantee any vendor an easy ride.
Abstract: Microsoft released a new version of OLE DB (Object Linking and Embedding Database, based on Microsoft’s Component Object Model or COM) which supports a proprietary data mining specification. It is purported to extend the Structured Query Language (SQL) to allow easier and faster incorporation of data mining queries into existing data warehouse solutions.
Abstract: Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.
Abstract: Managing performance means understanding results, setting metrics, fixing plans, and making decisions. Based on best practices, performance management (PM) solutions help coordinate planning, budgeting, reporting, analysis, ad hoc queries, dashboarding, and scorecarding to support decision-making. Learn how PM solutions facilitate the flow of the right information to the right people at the right time.
Abstract: Appliances are taking up permanent residence in the data warehouse (DW). The reason: they are preconfigured, support quick deployment, and accelerate online analytical processing (OLAP) queries against large, multidimensional data sets. Discover the core criteria you should use to evaluate DW appliances, including performance, functionality, flexibility, scalability, manageability, integration, and extensibility.
Abstract: To reduce time to market and realize the full value of its intellectual property, Cadbury plc needed to ensure compliance with government regulations. The company launched a long-term data management strategy, which included storing all data in a central repository—a product lifecycle management (PLM) system. Find out how Cadbury not only ensured compliance but also improved its response to consumer and customer queries.
Abstract: The old approaches for collecting, assimilating, and delivering business intelligence (BI) data have not kept pace with today’s increasing demand for rapid decision making. Many companies use static reports and ad hoc queries, but fewer companies use dashboards and portals—which often lack the interactivity required for navigation and visualization of business data. Learn how a next-generation dashboard solution can help.
Abstract: In order to achieve success, all business software projects have to surmount requirements risk, technical risk, and planning risk. Many software developers have thus adopted an iterative delivery methodology, finishing first the essential features, and then those additional features which deliver the most value. Some fundamental insights will provide a better understanding of how to set up iterative delivery projects.
Abstract: Getting lean is not a simple task; it requires an aggressive, iterative approach to examine complex tradeoffs. And given the number of variables that characterize a distribution center (DC) and its constituent stock keeping units (SKUs), performing this type of analysis without using the right tools can be daunting—if not impossible. Find out how a tool-based approach can make getting lean easier.